The thesis deals with the issue of measurement of frequency and its derivative (RoCoF) in simulation software. The aim of the thesis was to compare results obtained in three different pieces of software (PSS/E, PSCAD, MODES). 2 disturbances were simulated in a grid model IEEE 39 bus system and values of frequency and generator speed were assessed. The results obtained in different software are diverse. This is influenced by method of modelling of synchronous generator and algorithm of calculation of frequency. Findings are important for future investigation of power system transients in simulation software and also point to potencial incorrect assassement of frequency in protective relays.

This thesis is focused on voltage regulation in low voltage distribution system. It describes power management methods using photovoltaic inverters. The thesis describes the working PQ space of the inverter and the regulation characteristics of the active and reactive power in dependence on the voltage. The practical part focuses on the simulation of specific PQU control settings on the test models created in PSCAD. The model is used as a basis for real measurement. Outputs obtained from measurement and simulation are validated in the text. The last part of the thesis identifies limits for connecting resources with and without support.

The thesis deals with the comparison of two restoration paths in case of the black start in the MODES and PSCAD simulation programs. The aim was to compare the voltage waveforms in individual nodes and the system frequency. At the same time, simulations were compared with a real test. The route models in the MODES program were created earlier and the task was to create the same routes in the PSCAD program using the parameters available from the MODES program. The route models in the PSCAD environment included both the original and the new models of individual elements, which had to be assembled from function blocks. The results of the programs differed slightly, which was caused mainly by the differences of some elements that were used. In the thesis, all the necessary information was stated to make the simulations repeatable.

This work deals with the issue of evaluating transient stability in the simulation program PSCAD. Factors affecting transient stability were analyzed on a single-machine SMIB model. The results of this analysis confirmed the theoretical assumption that for more accurate results of the analysis of transient stability, it is necessary to consider the mentioned factors. A short circuit was simulated on the IEEE9 test model and subsequently the load angles of the generators were monitored using various methods. The method of reference of the largest generator in the system proved to be a more suitable method for the assessment of relative load angles from the results of the analysis.

This thesis aims to provide a recommended power system design for optimal efficiency, reliability, and cost in off-grid applications. The power system examined in this project is a residence in an off-grid community called Quail Springs that generates its energy from roof mounted solar panels. The existing system was analyzed to see what equipment can remain, what needs to be upsized, and what needs to be added to the system. Two power systems are considered for the residence: a fully AC power system and a hybrid AC/DC power system. Simulations were run in PSCAD to compare the efficiencies of the two proposed systems at varying load. The results of the simulations showed the hybrid power system to be generally less efficient when supplying AC and DC loads, but greater than 5% more efficient when only supplying DC load. Although the hybrid AC/DC system is approximately 70% more expensive, it is still the final recommended design due to potential efficiency gains and in an effort to provide educational opportunities that may lead to further efficiency gains in future hybrid AC/DC power systems.

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / O objetivo deste trabalho é conhecer e compreender melhor os imprevistos no fornecimento de energia elétrica, quando ocorrem as variações de tensão de curta duração (VTCD). O banco de dados necessário para os diagnósticos das faltas foi obtido através de simulações de um modelo de alimentador radial através do software PSCAD/EMTDC. Este trabalho utiliza um Phase-Locked Loop (PLL) com o intuito de detectar VTCDs e realizar a estimativa automática da frequência, do ângulo de fase e da amplitude das tensões e correntes da rede elétrica. Nesta pesquisa, desenvolveram-se duas redes neurais artificiais: uma para identificar e outra para localizar as VTCDs ocorridas no sistema de distribuição de energia elétrica. A técnica aqui proposta aplica-se a alimentadores trifásicos com cargas desequilibradas, que podem possuir ramais laterais trifásicos, bifásicos e monofásicos. No desenvolvimento da mesma, considera-se que há disponibilidade de medições de tensões e correntes no nó inicial do alimentador e também em alguns pontos esparsos ao longo do alimentador de distribuição. Os desempenhos das arquiteturas das redes neurais foram satisfatórios e demonstram a viabilidade das RNAs na obtenção das generalizações que habilitam o sistema para realizar a classificação de curtos-circuitos. / The objective of this work is to know and understand the unforeseen in the supply of electricity, when there are short duration voltage variations (SDVV). The required databases for the diagnosis of faults were obtained through simulations of a model of radial feeder through software PSCAD/EMTDC. This work uses a Phase-Locked Loop (PLL) in order to detect and perform the estimation SDVV automatic frequency, phase angle and amplitude of the voltage and current from the power grid. This research is developing two artificial neural networks: one to identify and another to locate the SDVV occurred in the distribution system of electricity. The technique proposed here applies to three-phase feeders with unbalanced loads, which can have side extensions triphasic, biphasic and monophasic. In developing the same, it is considered that there is availability of measurements of voltages and currents at the node of the initial feeder and also in some points scattered along the distribution feeder. The performances of the architectures of neural networks were satisfactory and demonstrate the feasibility of ANNs in obtaining the generalizations that enables the system for the classification of short circuits.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O objetivo deste trabalho é contribuir com o desenvolvimento de uma técnica baseada em sistemas inteligentes que possibilite a localização exata ou aproximada do ponto de origem de uma Variação de Tensão de Curta Duração (VTCD) (gerada por uma falta) em um sistema de distribuição de energia elétrica. Este trabalho utiliza um Phase-Locked Loop (PLL) com o intuito de detectar as faltas. Uma vez que a falta é detectada, os sinais de tensão obtidos durante a falta são decompostos em componentes simétricas instantâneas por meio do método proposto. Em seguida, as energias das componentes simétricas são calculadas e utilizadas para estimar a localização da falta. Nesta pesquisa, são avaliadas duas estruturas baseadas em Redes Neurais Artificiais (RNAs). A primeira é projetada para classificar a localização da falta em um dos pontos possíveis e a segunda é projetada para estimar a distância da falta ao alimentador. A técnica aqui proposta aplica-se a alimentadores trifásicos com cargas equilibradas. No desenvolvimento da mesma, considera-se que há disponibilidade de medições de tensões no nó inicial do alimentador e também em pontos esparsos ao longo da rede de distribuição. O banco de dados empregado foi obtido através de simulações de um modelo de alimentador radial usando o programa PSCAD/EMTDC. Testes de sensibilidade empregando validação-cruzada são realizados em ambas as arquiteturas de redes neurais com o intuito de verificar a confiabilidade dos resultados obtidos. Adicionalmente foram realizados testes com faltas não inicialmente contidas no banco de dados a fim de se verificar a capacidade de generalização das redes. Os desempenhos de ambas as arquiteturas de redes neurais foram satisfatórios e demonstram a viabilidade das técnicas propostas para realizar a localização de faltas em redes de distribuição. / The aim of this work is to contribute to the development of a technique based on intelligent systems that allows the accurate location of the Short Duration Voltage Variations (SDVV) origin in an electrical power distribution system. Once the fault is detected via a Phase-Locked Loop (PLL), voltage signals acquired during the fault are decomposed into instantaneous symmetrical components by the proposed method. Then, the energies of the symmetrical components are calculated and used to estimate the fault location. In this work, two systems based on Artificial Neural Networks (ANN) are evaluated. The first one is designed to classify the fault location into one of predefined possible points and the second is designed to estimate the fault distance from the feeder. The technique herein proposed is applies to three-phase feeders with balanced loads. In addition, it is considered that there is availability of voltage measurements in the initial node of the feeder and also in sparse points along the distribution power grid. The employed database was made using simulations of a model of radial feeder using the PSCAD / EMTDC program. Sensitivity tests employing cross-validation are performed for both approaches in order to verify the reliability of the results. Furthermore, in order to check the generalization capability, tests with faults not originally contained in the database were performed. The performances of both architectures of neural networks were satisfactory and they demonstrate the feasibility of the proposed techniques to perform fault location on distribution grids.

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / O objetivo deste trabalho é conhecer e compreender melhor os imprevistos no fornecimento de energia elétrica, quando ocorrem as variações de tensão de curta duração (VTCD). O banco de dados necessário para os diagnósticos das faltas foi obtido através de simulações de um modelo de alimentador radial através do software PSCAD/EMTDC. Este trabalho utiliza um Phase-Locked Loop (PLL) com o intuito de detectar VTCDs e realizar a estimativa automática da frequência, do ângulo de fase e da amplitude das tensões e correntes da rede elétrica. Nesta pesquisa, desenvolveram-se duas redes neurais artificiais: uma para identificar e outra para localizar as VTCDs ocorridas no sistema de distribuição de energia elétrica. A técnica aqui proposta aplica-se a alimentadores trifásicos com cargas desequilibradas, que podem possuir ramais laterais trifásicos, bifásicos e monofásicos. No desenvolvimento da mesma, considera-se que há disponibilidade de medições de tensões e correntes no nó inicial do alimentador e também em alguns pontos esparsos ao longo do alimentador de distribuição. Os desempenhos das arquiteturas das redes neurais foram satisfatórios e demonstram a viabilidade das RNAs na obtenção das generalizações que habilitam o sistema para realizar a classificação de curtos-circuitos. / The objective of this work is to know and understand the unforeseen in the supply of electricity, when there are short duration voltage variations (SDVV). The required databases for the diagnosis of faults were obtained through simulations of a model of radial feeder through software PSCAD/EMTDC. This work uses a Phase-Locked Loop (PLL) in order to detect and perform the estimation SDVV automatic frequency, phase angle and amplitude of the voltage and current from the power grid. This research is developing two artificial neural networks: one to identify and another to locate the SDVV occurred in the distribution system of electricity. The technique proposed here applies to three-phase feeders with unbalanced loads, which can have side extensions triphasic, biphasic and monophasic. In developing the same, it is considered that there is availability of measurements of voltages and currents at the node of the initial feeder and also in some points scattered along the distribution feeder. The performances of the architectures of neural networks were satisfactory and demonstrate the feasibility of ANNs in obtaining the generalizations that enables the system for the classification of short circuits.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O objetivo deste trabalho é contribuir com o desenvolvimento de uma técnica baseada em sistemas inteligentes que possibilite a localização exata ou aproximada do ponto de origem de uma Variação de Tensão de Curta Duração (VTCD) (gerada por uma falta) em um sistema de distribuição de energia elétrica. Este trabalho utiliza um Phase-Locked Loop (PLL) com o intuito de detectar as faltas. Uma vez que a falta é detectada, os sinais de tensão obtidos durante a falta são decompostos em componentes simétricas instantâneas por meio do método proposto. Em seguida, as energias das componentes simétricas são calculadas e utilizadas para estimar a localização da falta. Nesta pesquisa, são avaliadas duas estruturas baseadas em Redes Neurais Artificiais (RNAs). A primeira é projetada para classificar a localização da falta em um dos pontos possíveis e a segunda é projetada para estimar a distância da falta ao alimentador. A técnica aqui proposta aplica-se a alimentadores trifásicos com cargas equilibradas. No desenvolvimento da mesma, considera-se que há disponibilidade de medições de tensões no nó inicial do alimentador e também em pontos esparsos ao longo da rede de distribuição. O banco de dados empregado foi obtido através de simulações de um modelo de alimentador radial usando o programa PSCAD/EMTDC. Testes de sensibilidade empregando validação-cruzada são realizados em ambas as arquiteturas de redes neurais com o intuito de verificar a confiabilidade dos resultados obtidos. Adicionalmente foram realizados testes com faltas não inicialmente contidas no banco de dados a fim de se verificar a capacidade de generalização das redes. Os desempenhos de ambas as arquiteturas de redes neurais foram satisfatórios e demonstram a viabilidade das técnicas propostas para realizar a localização de faltas em redes de distribuição. / The aim of this work is to contribute to the development of a technique based on intelligent systems that allows the accurate location of the Short Duration Voltage Variations (SDVV) origin in an electrical power distribution system. Once the fault is detected via a Phase-Locked Loop (PLL), voltage signals acquired during the fault are decomposed into instantaneous symmetrical components by the proposed method. Then, the energies of the symmetrical components are calculated and used to estimate the fault location. In this work, two systems based on Artificial Neural Networks (ANN) are evaluated. The first one is designed to classify the fault location into one of predefined possible points and the second is designed to estimate the fault distance from the feeder. The technique herein proposed is applies to three-phase feeders with balanced loads. In addition, it is considered that there is availability of voltage measurements in the initial node of the feeder and also in sparse points along the distribution power grid. The employed database was made using simulations of a model of radial feeder using the PSCAD / EMTDC program. Sensitivity tests employing cross-validation are performed for both approaches in order to verify the reliability of the results. Furthermore, in order to check the generalization capability, tests with faults not originally contained in the database were performed. The performances of both architectures of neural networks were satisfactory and they demonstrate the feasibility of the proposed techniques to perform fault location on distribution grids.

Wind farms are commonly connected to the main grid through compensated lines which increases the power transfer capability of the line. Double Fed Induction Generator (DFIG) wind turbines in connection to compensated lines can experience Sub-Synchronous Control Interaction (SSCI) which can bring system quantities above allowed levels. The work conducted in this thesis describes the use of harmonic injection to analyze the DFIG. The method describes how to analyze the DFIG such that it can be used to determine if the DFIG will experience SSCI. By using Electro-Magnetic Transient (EMT) software, the work shows how the method can be used to analyze the DFIG both to find the resonant frequency as well as if the oscillations will be sufficiently damped or undamped. Using the method of harmonic injection, the DFIG’s internal control parameters are also investigated and the equivalent frequency dependant resistance of the system is measured. After analyzing the DFIG, a Power Oscillation Damper (POD) is implemented as a supplementary control system in the DFIG control system to dampen the SSCI. The POD is optimized using PSCAD and is validated using the harmonic injection method. / Vindkraftverk är vanligtvis anslutna till stamnätet genom kompenserade ledningar, vilket ökar ledningens effektöverföringsfaktor. Dubbelmatade induktionsgeneratorer (DFIG) i anslutning med kompenserade ledningar kan uppleva subsynkrona kontrollinteraktioner (SSCI) som kan leda till att vissa systemstorheter överskrider tillåtna nivåer. Det arbete som utförs i denna rapport beskriver användningen av harmonisk injektion för att analysera DFIG. Metoden beskriver hur man analyserar DFIG så att den kan användas för att avgöra om DFIG kommer att uppleva SSCI. Genom att använda EMT-programvara (Electro-Magnetic Transient) visar arbetet i rapporten hur metoden kan användas för att analysera DFIG både för att hitta resonansfrekvensen och för att avgöra om svängningarna kommer att vara tillräckligt dämpade eller odämpade. Med hjälp av metoden för harmonisk injektion undersöks också DFIG:s interna styrparametrar och systemets ekvivalenta frekvensberoende motstånd mäts. Efter analys av DFIG:en implementeras en dämptillsats (POD) som ett kompletterande styrsystem i DFIG:s styrsystem för att dämpa SSCI. POD optimeras med hjälp av PSCAD och valideras med hjälp av harmonisk injektionsmetod.